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Data quality assessment of interventional trials in public trial databases
Annabelle R Iken1, Rudolf W Poolman2, Maaike G J Gademan3
1Leiden University Medical Center, Department of Orthopaedics, Albinusdreef 2, Leiden, 2333 ZA, The Netherlands.
Journal of Clinical Epidemiology
|September 7, 2024
Summary
Data quality in total knee arthroplasty (TKA) trials registered on ClinicalTrials.gov (CTG) varies significantly. Ensuring reliable, accurate, and timely data is crucial for medical research and practice.
Area of Science:
- Clinical research methodology
- Data management in healthcare
- Orthopedic surgery outcomes
Background:
- High-quality data entry in clinical trial databases is essential for research validity and evidence-based medicine.
- Self-reported data in trial registries significantly impacts medical practice and future research.
- Assessing data quality in clinical trial registries is critical for reliable scientific findings.
Purpose of the Study:
- To evaluate the quality of self-reported data in clinical trial registries.
- To identify and assess data quality attributes including consistency, accuracy, completeness, and timeliness.
- To present systematic methods for evaluating data quality in healthcare databases.
Main Methods:
- Searched ClinicalTrials.gov (CTG) for interventional total knee arthroplasty (TKA) trials (2000-2015).
- Extracted required and optional trial information elements using CTG definitions.
- Conducted a literature review on data quality reporting frameworks and identified data irregularities.
Main Results:
- Included 816 interventional TKA trials; data irregularities varied widely (0%-100%).
- Inconsistency (0%-36%), inaccuracy (0%-100%), and incompleteness (0%-61%) were observed.
- 49% of trials registered over 3 months late; 61% of completed trials failed to report outcomes.
Conclusions:
- Significant variations in data quality exist among registered clinical TKA trials.
- Trial sponsors must ensure data reliability, consistency, accuracy, and timeliness.
- Users of trial registries should critically evaluate registered data for informed decision-making.
Keywords:
Clinical trialsData quality assessmentData structuresDecision-makingInformation managementQuality managementMore Related Videos
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